typealias / abstract deps

src/dims/seq.jl

@@ -17,4 +17,4 @@ convert{T,S}(::Type{Seq{T,S}},storage::S) =
        Juno.trim(collect(b)))
 end
 
-typealias BatchSeq{T<:Seq} Batch{T}
+BatchSeq{T<:Seq} = Batch{T}

src/layers/shape.jl

@@ -1,6 +1,6 @@
 export Input
 
-typealias Dims{N} NTuple{N,Int}
+Dims{N} = NTuple{N,Int}
 
 dims(d::Dims) = d
 

src/model.jl

@@ -15,7 +15,7 @@ where `W` and `b` are a trainable matrix and vector of weights repectively. The
 closer to a protocol, and models don't need to inherit from this type. Normal
 Julia functions are models with 0 parameters, for example.
 """
-abstract Model
+abstract type Model end
 
 """
     back!(m::Model, ΔY, X...) => ΔX